comparison hicTransform.xml @ 4:d5bf6e7d3800 draft

planemo upload for repository https://github.com/maxplanck-ie/HiCExplorer/tree/master/galaxy/wrapper/ commit eec0a4d5a7c5ba4ec0fbd2ead8280c3d143bb9d8

3:303558d3bc11

<tool id="hicexplorer_hictransform" name="@BINARY@" version="@WRAPPER_VERSION@.0">
    <description>transforms a matrix to a obs_exp, pearson and covariance matrix</description>
    <macros>
        <token name="@BINARY@">hicTransform</token>
        <import>macros.xml</import>
    </macros>
    <expand macro="requirements" />

            <option value="cool">cool</option>
        </param>

    </inputs>
    <outputs>
        <data name="obs_exp" from_work_dir="obs_exp_matrix" format="h5">
            <change_format>
                <when input="outputFormat" value="cool" format="cool" />
            </change_format>
        </data>
        <data name="pearson" from_work_dir="pearson_matrix" format="h5">
            <change_format>
                <when input="outputFormat" value="cool" format="cool" />
            </change_format>
        </data>
        <data name="covariance" from_work_dir="covariance_matrix" format="h5">
            <change_format>
                <when input="outputFormat" value="cool" format="cool" />
            </change_format>
        </data>

    </outputs>
    <tests>

        </test>
    </tests>
    <help><![CDATA[
Transformation of matrix for plotting
=====================================
`hicTransform` computes three matrices: an observed/expected matrix based on it a
pearson correlation matrix and based on it a covariance matrix. These three matrices
can be used with `hicPlotMatrix` for an A / B compartment analysis.

Input
-----
- the matrix to be transformed

Parameters
__________
- Output file format: h5 or cool

Output
------
- observed/expected matrix
- pearson correlation matrix 
- covariance matrix.

| For more information about HiCExplorer please consider our documentation on readthedocs.io_

.. _readthedocs.io: http://hicexplorer.readthedocs.io/en/latest/index.html
]]></help>
    <expand macro="citations" />
</tool>

4:d5bf6e7d3800

<tool id="hicexplorer_hictransform" name="@BINARY@" version="@WRAPPER_VERSION@.0">
    <description>transform a matrix to obs/exp, pearson and covariance matrices</description>
    <macros>
        <token name="@BINARY@">hicTransform</token>
        <import>macros.xml</import>
    </macros>
    <expand macro="requirements" />

            <option value="cool">cool</option>
        </param>

    </inputs>
    <outputs>
        <data name="obs_exp" from_work_dir="obs_exp_matrix" format="h5" label="${tool.name} on ${matrix_h5_cooler.name} [${on_string}]: Observed/Expected matrix">
            <change_format>
                <when input="outputFormat" value="cool" format="cool"/>
            </change_format>
        </data>
        <data name="pearson" from_work_dir="pearson_matrix" format="h5" label="${tool.name}  on ${matrix_h5_cooler.name} [${on_string}]: Pearson matrix">
            <change_format>
                <when input="outputFormat" value="cool" format="cool"/>
            </change_format>
        </data>
        <data name="covariance" from_work_dir="covariance_matrix" format="h5" label="${tool.name} on ${matrix_h5_cooler.name} [${on_string}]: Covariance matrix">
            <change_format>
                <when input="outputFormat" value="cool" format="cool"/>
            </change_format>
        </data>

    </outputs>
    <tests>

        </test>
    </tests>
    <help><![CDATA[
Transformation of matrix for plotting
=====================================

**hicTransform** computes three matrices based on one Hi-C contact matrix as input based on the methods determined by `Lieberman-Aiden et al. (2009)`_:

- An **observed/expected matrix** obtained "by dividing each entry in the contact matrix by the genome-wide average contact probability for loci at that genomic distance" (`Lieberman-Aiden et al. (2009)`_). This transformation allows to better assess long range interactions.
- A **Pearson correlation matrix** obtained by computing the Pearson correlation between each bin based on observed/expected values. This matrix transformation allows to better identify the bins that are entering in contact together, or not, at long ranges, and thus helps defining compartments in the nucleus (``hicPCA``).
- A **covariance matrix**, which is used as a basis for the Principal Component Analysis (PCA) to compute the eigenvectors outputed by **hicTransform**.

These three matrices can be used with ``hicPlotMatrix`` or ``hicPlotTADs`` for a visualization of the A / B compartment analysis.

_________________

Output
------

From one Hi-C contact matrix, **hicTransform** outputs the observed/expected, Pearson correlation and covariance matrices.

_________________

| For more information about HiCExplorer please consider our documentation on readthedocs.io_

.. _readthedocs.io: http://hicexplorer.readthedocs.io/en/latest/index.html
.. _`Lieberman-Aiden et al. (2009)`: https://dx.doi.org/10.1126%2Fscience.1181369
]]></help>
    <expand macro="citations" />
</tool>